Description Usage Arguments Value Examples
Test gene sets for unidirectional enrichment
1 2 3 | testUnidirectionality(barycoords, gsets, Gdiffexp = NULL,
statistic = "diffexp", bm = NULL, minknown = 5, mindiffexp = 0,
maxknown = 1500, mc.cores = getOption("mc.cores", default = 1), ...)
|
barycoords |
Dataframe containing for every gene its barycentric coordinates, as returned by |
gsets |
List of character vectors, each containing a set of genes (gene identifiers) |
Gdiffexp |
Differentially expressed genes |
statistic |
A string denoting the measure used for the strength of upregulation of a particular gene.
|
bm |
Previously calculated background model using the |
minknown |
Minimal number of genes within a gene set for it to be considered for enrichment |
mindiffexp |
Minimal number of genes differentially expressed within a gene set for it to be considered for enrichment |
maxknown |
Maximal number of genes within a gene set for it to be considered for enrichment |
mc.cores |
Number of processor cores to use. Due to limitations of the parallel package, this does not work on Windows |
... |
Parameters for |
Dataframe containing for every gene set which passed the filtering:
p-value of unidirectionality
q-value of unidirectionality (p-value corrected for multiple testing)
average angle
1 2 3 4 5 6 | Eoi = matrix(rnorm(1000*3, sd=0.5), 1000, 3, dimnames=list(1:1000, c(1,2,3)))
Eoi[1:100,1] = Eoi[1:100,1] + 4 # the first 100 genes are more upregulated in the first condition
barycoords = transformBarycentric(Eoi)
gsets = list(a=1:50, b=80:150, c=200:500)
testUnidirectionality(barycoords, gsets, Gdiffexp=(1:1000)[barycoords$r > 1])
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